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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

Computing observation geometry for small satellites

Most solar system science missions need a variety of observation geometry–quantities such as position and velocity, range and altitude, viewing latitude and longitude, and lighting angles– to support mission engineering, science planning, and science data analysis activities. NASA's "SPICE" system offers one popular, multi-mission means for doing just that. SPICE comprises both data files, called kernels, and a SPICE software Toolkit that is available in many popular languages. A mission operations center produces the SPICE kernel files. Scientists and engineers write their own applications programs to address some need, and they include a few SPICE subroutines within that code to do the needed geometry computations. The SPICE system has been in use throughout NASA’s planetary science mission domain since 1991, and it has slowly spread to most major space agencies around the globe since then. The SPICE software is available in most popular languages, and for most popular platforms. The code is thoroughly tested before being released, and new versions of the Toolkit are always backwards compatible. The SPICE components are freely offered to everyone, and have no export, licensing or similar restrictions. Maybe using SPICE would work for your CubeSat or SmallSat mission?

Acton, Charles H.↗
DOE OSTI2021

Binary Complex Neural Network Acceleration on FPGA

Being able to learn from complex data with phase information is imperative for many signal processing applications. Today’s real-valued deep neural networks (DNNs) have shown efficiency in latent information analysis but fall short when applied to the complex domain. Deep complex networks (DCN) , in contrast, can learn from complex data, but have high computational costs; therefore, they cannot satisfy the instant decision making requirements of many deployable systems dealing with short observations or short signal bursts. Recent, Binarized Complex Neural Network (BCNN), which integrates DCNs with binarized neural networks (BNN), shows great potential in classifying complex data in real-time. In this paper, we propose a structural pruning based accelerator of BCNN, which is able to provide more than 5000 frames/s inference throughput on edge devices. The high performance comes from both the algorithm and hardware sides. On the algorithm side, we conduct structural pruning to the original BCNN models and obtain 20 × pruning rates with negligible accuracy loss; on the hardware side, we propose a novel 2D convolution operation accelerator for the binary complex neural network. Experimental results show that the proposed design works with over 90% utilization and is able to achieve the inference throughput of 5882 frames/s and 4938 frames/s for complex NIN-Net and ResNet-18 using CIFAR-10 dataset and Alveo U280 Board.

Peng, Hongwu↗
DOE OSTI2024

Exploring Architectural-Aware Affinity Policies in Modern HPC Runtimes

Modern commodity and High-Performance Computing (HPC) systems are evolving with complex CPU architectures. These architectures now feature higher core and NUMA domain counts and implement features such as hyperthreading. When considering significant differences in hardware configurations, library availability, and hardware-tailored system/software stacks, which could substantially vary from one system to another, performance portability is hard to achieve. Throughout the years, this trend resulted in an increasingly high burden on application developers to fine-tune their workloads for each architecture. This work explores how hardware-dependent aspects such as locality/process/thread affinity affect performance in modern CPU architectures. We focus our study on the Global Memory and Threading (GMT) distributed runtime system as a representative of Partitioned Global Address Space (PGAS) software stacks commonly adopted for productivity. In particular, to appreciate performance implications, we evaluate GMT’s thread affinity policies, and, introduce two new ones which exploit architectural awareness. Finally, we explore alternative NUMA configurations via different process bindings and perform a scalability study on three HPC clusters with varying CPU architectures and NUMA layouts. Our analysis indicates that more complex architectures are more affected by affinity and binding policies and highlights the importance of setting proper runtime configurations to achieve superior performance.

Di Dio Lavore, Ian↗
DOE OSTI2020

TriC: Distributed-memory Triangle Counting by Exploiting the Graph Structure

Graph analytics has emerged as an important tool in the analysis of large scale data from diverse application domains such as social networks, cyber security and bioinformatics. Counting the number of triangles in a graph is a fundamental kernel with several applications such as detecting the community structure of a graph or in identifying important vertices in a graph. The ubiquity of massive datasets is driving the need to scale graph analytics on parallel systems. However, numerous challenges exist in efficiently parallelizing graph algorithms, especially on distributed-memory systems. Irregular memory accesses and communication patterns, low computation to communication ratios, and the need for frequent synchronization are some of the leading challenges. In this paper, we present TriC, our distributed-memory implementation of triangle counting in graphs using the Message Passing Interface (MPI), as a submission to the 2020 GraphChallenge competition. Using a set of synthetic and real-world inputs from the challenge, we demonstrate a speedup of up to 90x relative to previous work on 32 processor-cores of a NERSC Cori node. We also provide details from distributed runs with up to8192 processes along with strong scaling results. The observations presented in this work provide an understanding of the system-level bottlenecks at scale that specifically impact sparse-irregular workloads and will therefore benefit other efforts to parallelize graph algorithms.

Halappanavar, Mahantesh↗
DOE OSTI2015

Ternary eutectic dendrites: Pattern formation and scaling properties

Extending previous work [Pusztai et al., Phys. Rev. E 87, 032401 (2013)], we have studied the formation of eutectic dendrites in a model ternary system within the framework of the phase-field theory. We have mapped out the domain in which two-phase dendritic structures grow. With increasing pulling velocity, the following sequence of growth morphologies is observed: flat front lamellae → eutectic colonies → eutectic dendrites → dendrites with target pattern → partitionless dendrites → partitionless flat front. We confirm that the two-phase and one-phase dendrites have similar forms and display a similar scaling of the dendrite tip radius with the interface free energy. It is also found that the possible eutectic patterns include the target pattern, and single- and multiarm spirals, of which the thermal fluctuations choose. The most probable number of spiral arms increases with increasing tip radius and with decreasing kinetic anisotropy. Our numerical simulations confirm that in agreement with the assumptions of a recent analysis of two-phase dendrites [Akamatsu et al., Phys. Rev. Lett. 112, 105502 (2014)], the Jackson-Hunt scaling of the eutectic wavelength with pulling velocity is obeyed in the parameter domain explored, and that the natural eutectic wavelength is proportional to the tip radius of the two-phase dendrites. Finally, we find that it is very difficult/virtually impossible to form spiraling two-phase dendrites without anisotropy, an observation that seems to contradict the expectations of Akamatsu et al. Yet, it cannot be excluded that in isotropic systems, two-phase dendrites are rare events difficult to observe in simulations.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Evaluating Contributions of Pitch-Carbon Coating to Improved Stability of Si Anodes Through Voltage-Resolved Multi-Phase Characterization

Silicon nanoparticles have emerged as a promising alternative to graphite to improve the energy density of next-generation lithium-ion battery anodes. Nano-sized Si domains facilitate rapid ion transport and minimize particle-scale mechanical degradation, but also exhibit increased (electro)chemical reactivity with Li-ion electrolyte components due to their high surface area. We have previously demonstrated that surface modification of Si nanoparticles with pitch-carbon is an effective strategy to reduce these parasitic reactions. In the present work, we holistically evaluate the mechanistic contribution of pitch-carbon coating to the observed stability improvement over uncoated Si. We utilize coupled in situ and ex situ methods to probe changes to solid-surface, volatile headspace, and gas-phase chemistry occurring during initial cycling. Measurements taken at targeted potentials associated with electrolyte species reduction enables the decoupling of specific reaction pathways tied to interfacial stability. Further, we demonstrate the non-trivial role of gas reconsumption in dictating the nature of the passivating surface layer evolved on both uncoated and pitch-coated Si. This multi-phase analysis offers insights into the mechanism of effective surface passivation, which may be applied to inform future Si material development.

ENERGY STORAGE↗
DOE OSTI2025

Solid State Transformer Architecture and Control Compensation for Common Mode Currents

A high-altitude electromagnetic pulse (HEMP) or similar geomagnetic disturbance (GMD) has the potential to impact the operation of large-scale electric power grids. By introducing low-frequency common-mode (CM) currents, these events can degrade the performance of critical system components, such as large power transformers by introducing CM currents which can lead to magnetic saturation of the transformer core. In this work, a solid-state transformer (SST) is developed to replace susceptible equipment and improve grid resiliency by safely absorbing these CM disturbances. This device will be referred to as a common-mode solid-state transformer (CM-SST). An SST architecture based on a four-legged AC/DC converter is developed. This architecture enables active control of CM signals without disturbing the AC voltages or the real and reactive power delivery capabilities. A system-level model of this architecture is created, and time-domain simulations are performed to evaluate the SST’s performance in response to simulated CM disturbances. A control strategy for mitigating CM current is also investigated. Hamiltonian surface shaping and power flow control (HSSPFC) is used to design a nonlinear controller for the SST’s output inverter. The objectives of the controller are to suppress CM-induced AC current offsets and regulate AC currents to desired setpoints. Nonlinear system analysis is applied to design and validate the controller. Two cases are tested: (a) the proposed four-leg inverter and (b) a standard three-leg inverter. The results show that the proposed controller rapidly mitigates CM disturbances while maintaining high-quality AC current waveforms in the four-leg configuration. Finally, the hardware performance of an SST prototype is evaluated. In particular, the ability of the SST to safely redirect and absorb CM currents is demonstrated, showing how it can protect neighboring conventional transformers in the system. The study confirms that appropriate control laws allow the SST to protect both itself and adjacent transformers during a HEMP or GMD event.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

High-moisture pelleting of corn stover using pilot- and commercial-scale systems: Impact of moisture content, L / D ratio and hammer mill screen size on pellet quality and energy consumption

Here, high-moisture pelleting of corn stover was tested in pilot- and commercial-scale systems. For the pilot-scale study, a 6.35 mm screen size hammer mill ground corn stover was reconditioned to moisture between 14 and 29.6% (w.b.), and 5, 7 and 9 L/D ratio pellet die were used. At 29% corn stover moisture content and L/D ratios of 5 and 9, the bulk density and durability of the pellets were ≤450 kg/m 3 and <90% and >540 kg/m 3 and >90%, respectively. Increasing the feedstock moisture and L/D ratio increased the pelleting energy. Increasing the hammer mill screen size to 11.11 mm reduced the bulk density but not the durability. The response surface models adequately described the pelleting process (R 2 ≥ 0.88), and analysis of variance showed a strong interaction between the process variables and pellet properties. Commercial-scale testing of high-moisture pelleting using 6.35 mm ground corn stover bales in the moisture range 24–26% (w.b.) produced pellets with a density of >675 kg/m 3 and durability of >98%, whereas increasing the hammer mill screen size to 11.11 mm reduced the bulk density by about 100 kg/m 3 but not the durability. The energy consumption of the commercial-scale unit operations for the high-moisture pelleting process was in the range 98–124 kW h/ton, which is 64–72% less energy than conventional pelleting that requires energy about 350 kW h/ton for biomass drying from 30% (w.b.) to 10% (w.b.) moisture content before pelleting. Pellets produced using high-moisture pelleting met International Organization for Standardization and Pellets Fuel Institute international standards. Published 2023. This article is a U.S. Government work and is in the public domain in the USA.

09 BIOMASS FUELS↗
NASA NTRS2006

Tracking Energy Flow Using a Volumetric Acoustic Intensity Imager (VAIM)

A new measurement device has been invented at the Naval Research Laboratory which images instantaneously the intensity vector throughout a three-dimensional volume nearly a meter on a side. The measurement device consists of a nearly transparent spherical array of 50 inexpensive microphones optimally positioned on an imaginary spherical surface of radius 0.2m. Front-end signal processing uses coherence analysis to produce multiple, phase-coherent holograms in the frequency domain each related to references located on suspect sound sources in an aircraft cabin. The analysis uses either SVD or Cholesky decomposition methods using ensemble averages of the cross-spectral density with the fixed references. The holograms are mathematically processed using spherical NAH (nearfield acoustical holography) to convert the measured pressure field into a vector intensity field in the volume of maximum radius 0.4 m centered on the sphere origin. The utility of this probe is evaluated in a detailed analysis of a recent in-flight experiment in cooperation with Boeing and NASA on NASA s Aries 757 aircraft. In this experiment the trim panels and insulation were removed over a section of the aircraft and the bare panels and windows were instrumented with accelerometers to use as references for the VAIM. Results show excellent success at locating and identifying the sources of interior noise in-flight in the frequency range of 0 to 1400 Hz. This work was supported by NASA and the Office of Naval Research.

Klos, Jacob↗
NASA NTRSDate not supplied

Developing a Vision for Heliophysics Infrastructure: The LIKED Resource and the DIARieS Ecosystem

Heliophysics data and computational infrastracture are not equipped for 21st science, suffering from holes in the know-how to build better systems. Without a clear vision, efforts to improve the infrastructure have been incremental and incoherent. This poster presents both the vision and the technology required: an online LIbrary KnowledgE and Discovery (LIKED) resource for discovering and implementing knowledge, data, and infrastructure resources; and an online analysis ecosystem to simplify Discovery, Implementation, Analysis, Reproducibility, and Sharing (DIARieS) of scientific results and environments. The LIKED and DIARieS solutions adopt FAIR data principles and the best practices from the budding field of open science. The proposed new infrastructure components will close many of the current gaps in heliophysics’ infrastructure, such as the ability to search for data and knowledge by phenomenon across domains, and to find software and examples relevant to the desired data set (including model data). Further, these components will enable community members to more efficiently use the resources already present and improve upon the content via a community-curated and trusted library. Combining these solutions lowers the barriers to heliophysics resources for all, increasing the return on our investments. Finally, the structure behind these ideas are topic-agnostic, so they are fully extensible to other fields, leading to invaluable connections to other disciplines. Just as with the development and construction of a long-term satellite mission, we must work together as a community to build a vision of the infrastructure that will most benefit the community, and then collaborate to construct, assemble, and test all the necessary pieces individually and as a unit. Our purpose in presenting this work is to not only describe the proposed vision, but also to gather feedback from the community on this topic.

infrastructure↗
NASA NTRSDate not supplied

CFD Predictions of Fluctuating Pressure Environments on NASA’s SLS Ascent Unsteady Aerodynamics Wind Tunnel Test

This paper details work that is being conducted on predicting fluctuating pressure environments on NASA launch vehicles using computational fluid dynamics (CFD). The accurate characterization of these aeroacoustics environments is necessary in the analysis of vehicle structural health and aerodynamic performance and in the vehicle design process. High-fidelity simulations of the unsteady flow over NASA’s SLS Ascent Unsteady Aerodynamics wind tunnel Test (AUAT) using the hybrid Reynolds-averaged Navier-Stokes (RANS)-large eddy simulations (LES) methodologies in Mississippi States’ Loci/CHEM solver are presented. The two available methods, Nelson-Nichols and dynamic hybrid RANS-LES (DHRL), are compared head-to-head on identical grids at two Mach numbers. At the high-subsonic Mach number, locally supersonic flow expanding over a shoulder induces a separation-reattachment system that is predicted poorly by the Nelson-Nichols method due to an under-prediction in unsteady content. The DHRL solution predicts the spatial extent and frequency domain response of this system well but under-predicts the peak noise levels due to a delay in the RANS-to-LES transition. At the low-supersonic Mach number, compression corner dynamics dominate the unsteady flow. While the Nelson Nichols solution captures this phenomenon well, another solution on a refined grid indicates that some model stress depletion is occurring. The DHRL solution again performs well at this Mach number and matches the wind tunnel data fairly closely, but perhaps most impressively, is fairly agnostic to increasing grid resolution. The findings in this paper are expected to be generally applicable and will be used to guide the prediction of aeroacoustics environments of other NASA launch vehicles.

CFD↗
DOE OSTI2016

Nucleon resonance structure studies via exclusive KY electroproduction

Studying the structure of excited nucleon states employing the electroproduction of exclusive reactions is an important avenue for exploring the nature of the non-perturbative strong interaction. The electrocouplings of $N^*$ states in the mass range below 1.8~GeV have been determined from analyses of CLAS $\pi N$, $\eta N$, and $\pi \pi N$ data. This work has made it clear that consistent results from independent analyses of several exclusive channels with different couplings and non-resonant backgrounds but the same $N^*$ electro excitation amplitudes, is essential to have confidence in the extracted results. In terms of hadronic coupling, many high-lying $N^*$ states preferentially decay through the $\pi \pi N$ channel instead of $\pi N$. Data from the $KY$ channels will therefore be critical to provide an independent analysis to compare the extracted electrocouplings for the high-lying $N^*$ states against those determined from the $\pi N$ and $\pi \pi N$ channels. Lastly, a program to study excited $N^*$ state structure in both non-strange and strange exclusive electroproduction channels using CLAS12 will measure differential cross sections and polarization observables to be used as input to extract the $\gamma_vNN^*$ electrocoupling amplitudes for the most prominent $N^*$ states in the range of invariant energy $W$ up 3~GeV in the virtually unexplored domain of momentum transfers $Q^2$ up to 12~GeV$^2$.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

A new elliptical-beam method based on time-domain thermoreflectance (TDTR) to measure the in-plane anisotropic thermal conductivity and its comparison with the beam-offset method

Materials lacking in-plane symmetry are ubiquitous in a wide range of applications such as electronics, thermoelectrics, and high-temperature superconductors, in all of which the thermal properties of the materials play a critical part. Yet, very few experimental techniques can be used to measure in-plane anisotropic thermal conductivity. A beam-offset method based on time-domain thermoreflectance (TDTR) was previously proposed to measure in-plane anisotropic thermal conductivity. However, a detailed analysis of the beam-offset method is still lacking. Our analysis shows that uncertainties can be large if the laser spot size or the modulation frequency is not properly chosen. In this report we propose an differing approach based on TDTR to measure in-plane anisotropic thermal conductivity using a highly elliptical pump (heating) beam. The highly elliptical pump beam induces a quasi-one-dimensional temperature profile on the sample surface that has a fast decay along the short axis of the pump beam. The detected TDTR signal is exclusively sensitive to the in-plane thermal conductivity along the short axis of the elliptical beam. By conducting TDTR measurements as a function of delay time with the rotation of the elliptical pump beam to different orientations, the in-plane thermal conductivity tensor of the sample can be determined. In this work, we first conduct detailed signal sensitivity analyses for both techniques and provide guidelines in determining the optimal experimental conditions. We then compare the two techniques under their optimal experimental conditions by measuring the in-plane thermal conductivity tensor of a ZnO [11-20] sample. The accuracy and limitations of both methods are discussed.

47 OTHER INSTRUMENTATION↗
DOE OSTI2013

THE APPLICATION OF CONTINUOUS WAVELET TRANSFORM BASED FOREGROUND SUBTRACTION METHOD IN 21 cm SKY SURVEYS

We propose a continuous wavelet transform based non-parametric foreground subtraction method for the detection of redshifted 21 cm signal from the epoch of reionization. This method works based on the assumption that the foreground spectra are smooth in frequency domain, while the 21 cm signal spectrum is full of saw-tooth-like structures, thus their characteristic scales are significantly different. We can distinguish them in the wavelet coefficient space easily and perform the foreground subtraction. Compared with the traditional spectral fitting based method, our method is more tolerant to complex foregrounds. Furthermore, we also find that when the instrument has uncorrected response error, our method can also work significantly better than the spectral fitting based method. Our method can obtain similar results with the Wp smoothing method, which is also a non-parametric method, but our method consumes much less computing time.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Software Verification of VARPOW

The VARPOW program is a post-processing utility program for DIF3D, specifically DIF3DVARIANT, and it was developed to provide interface files for the thermal analysis program DASSH. The basic methodology of VARPOW is to take the neutron and gamma flux (moments) calculated by DIF3D (or GAMSOR) and combine them with the heating (coefficient) cross sections to calculate the spatial power distributions using the DIF3DVARIANT spatial basis. VARPOW can use the output from GAMSOR (both steady state neutron and gamma flux calculations) or standard DIF3D/REBUS calculations (neutron flux only). The correct approach for defining the power distribution is to use GAMSOR as its purpose was to properly compute the gamma heating throughout the modeled domain. The power densities calculated by VARPOW are broken into fuel, cladding and coolant terms for which isotope-wise categorization is needed. VARPOW has built in options the user can select for the isotope categorization or VARPOW can import a file that details the isotope categorization. VARPOW can export the solution in the polynomial basis of DIF3D-VARIANT or the monomial basis of DIF3D-VARIANT. The purpose of this work is to verify the power distribution results calculated by VARPOW from both the GAMSOR and DIF3D input options and verify that the input and output options are consistent with the manual. Hand calculation and independent numerical calculation are used for this verification work.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Software Verification of VARPOW

The VARPOW program is a post-processing utility program for DIF3D, specifically DIF3DVARIANT, and it was developed to provide interface files for the thermal analysis program DASSH. The basic methodology of VARPOW is to take the neutron and gamma flux (moments) calculated by DIF3D (or GAMSOR) and combine them with the heating (coefficient) cross sections to calculate the spatial power distributions using the DIF3DVARIANT spatial basis. VARPOW can use the output from GAMSOR (both steady state neutron and gamma flux calculations) or standard DIF3D/REBUS calculations (neutron flux only). The correct approach for defining the power distribution is to use GAMSOR as its purpose was to properly compute the gamma heating throughout the modeled domain. The power desnities calculated by VARPOW are broken into fuel, cladding and coolant terms for which isotope-wise categorization is needed. VARPOW has built in options the user can select for the isotope categorization or VARPOW can import a file that details the isotope categorization. VARPOW can export the solution in the polynomial basis of DIF3D-VARIANT or the monomial basis of DIF3D-VARIANT. The purpose of this work is to verify the power distribution results calculated by VARPOW from both the GAMSOR and DIF3D input options and verify that the input and output options are consistent with the manual. Hand calculation and independent numerical calculation are used for this verification work.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

BuildingQA: A Benchmark for Natural Language Question Answering over Building Knowledge Graphs

Graph-based representations of building metadata using ontologies like Brick are vital for smart building applications, but querying them remains a challenge for practitioners. Knowledge Graph Question Answering (KGQA) systems, meant to retrieve answers from natural language questions, traditionally require large-scale training data, making them ill-suited for the specialized and data-scarce building domain. The advent of Large Language Models (LLMs) offers a paradigm shift, enabling zero-shot natural language querying without building/domain-specific training. Yet, there is no standardized benchmark for building-specific KGQA which can guide and validate research in this area. To address this gap, our work makes three primary contributions. First, we introduce the BuildingQA Benchmark Dataset, constructed through a multi-stage process of collecting practitioner data, augmenting it with LLMs for linguistic diversity, and curating a final set of 188 questions across 4 buildings. Second, we characterize the benchmark's complexity and ambiguity, introducing a novel method to quantify its "lexical gap" and providing a four-stage diagnostic framework for analyzing how systems fail. Third, we benchmark zero-shot LLM-powered KGQA systems to establish baseline performance and analyze their failure modes. Our evaluation reveals that top-performing systems achieve a maximum F1 score of only 0.38. This result does not indicate a failure of these powerful systems, but rather underscores the unique challenges posed by our benchmark. It demonstrates a critical performance gap, showing that current methods successful on general KGs struggle with the specific lexical and structural nuances of the building domain. BuildingQA1 thus provides the benchmark dataset and foundational analysis needed to drive the development of novel, domain-aware methods required to unlock the use of semantic data in buildings.

Mulayim, Ozan Baris↗
DOE OSTI2025

Deploying Adversarial Attacks in Super-Resolution Models

Reliable super-resolution methods are crucial for applications like remote sensing, grid resilience and disaster impact analysis, and standoff biometrics. These methods infuse additional high-frequency information into reconstructions, allowing for better contextualization and image intelligence. However, super-resolution models can also introduce hallucinations or other unseen vulnerabilities that could be exploited by an adversary. This is further compounded by the prominence of deep learning in these models, as models are often blindly applied on out-of-distribution images. In this work, we implement adversarial attacks in common open-source super-resolution models and examine their impact on reconstructions and downstream classification tasks. We find that an adversarially trained super-resolution model can produce high-quality reconstructions that degrade downstream classifications. Moreover, these attacks do not require access to low-resolution imagery or class labels at inference time. These results demonstrate the vulnerability of super-resolution methods to malicious actors and motivates the development of a detector for super-resolution adversarial attacks. Further exploration of adversarial attacks in this domain is required to ensure trustworthiness and robustness of super-resolution models for national security applications.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗